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    [21]:
    import pandas as pd
    import matplotlib.pyplot as plt
    df = pd.read_csv("universities.csv")
    df
    [21]:
    Univ SAT Top10 Accept SFRatio Expenses GradRate
    0 Brown 1310 89 22 13 22704 94
    1 CalTech 1415 100 25 6 63575 81
    2 CMU 1260 62 59 9 25026 72
    3 Columbia 1310 76 24 12 31510 88
    4 Cornell 1280 83 33 13 21864 90
    5 Dartmouth 1340 89 23 10 32162 95
    6 Duke 1315 90 30 12 31585 95
    7 Georgetown 1255 74 24 12 20126 92
    8 Harvard 1400 91 14 11 39525 97
    9 JohnsHopkins 1305 75 44 7 58691 87
    10 MIT 1380 94 30 10 34870 91
    11 Northwestern 1260 85 39 11 28052 89
    12 NotreDame 1255 81 42 13 15122 94
    13 PennState 1081 38 54 18 10185 80
    14 Princeton 1375 91 14 8 30220 95
    15 Purdue 1005 28 90 19 9066 69
    16 Stanford 1360 90 20 12 36450 93
    17 TexasA&M 1075 49 67 25 8704 67
    18 UCBerkeley 1240 95 40 17 15140 78
    19 UChicago 1290 75 50 13 38380 87
    20 UMichigan 1180 65 68 16 15470 85
    21 UPenn 1285 80 36 11 27553 90
    22 UVA 1225 77 44 14 13349 92
    23 UWisconsin 1085 40 69 15 11857 71
    24 Yale 1375 95 19 11 43514 96
    [23]:
    s2 = [20,30,40,50,60,70,90,55,66,77,]
    scores2 = pd.Series(s2)
    print(scores2)
    plt.figure(figsize=(6,2))
    plt.title("Boxplot for batsman scores")
    plt.xlabel("Scores")
    plt.boxplot(scores2, vert = False)
    0    20
    1    30
    2    40
    3    50
    4    60
    5    70
    6    90
    7    55
    8    66
    9    77
    dtype: int64
    
    [23]:
    {'whiskers': [<matplotlib.lines.Line2D at 0x1c99c620980>,
      <matplotlib.lines.Line2D at 0x1c99c620cb0>],
     'caps': [<matplotlib.lines.Line2D at 0x1c99c620f50>,
      <matplotlib.lines.Line2D at 0x1c99c621250>],
     'boxes': [<matplotlib.lines.Line2D at 0x1c99c620770>],
     'medians': [<matplotlib.lines.Line2D at 0x1c99c621520>],
     'fliers': [<matplotlib.lines.Line2D at 0x1c99c621820>],
     'means': []}
    [ ]:

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